Advancements in Locoregional Therapies for Unresectable Intrahepatic Cholangiocarcinoma
Bibliographic record
Abstract
Intrahepatic cholangiocarcinoma is an aggressive malignancy with rising incidence and poor outcomes. This review examines recent advancements in locoregional therapies for unresectable intrahepatic cholangiocarcinoma, focusing on external beam radiotherapy, transarterial radioembolization (TARE), hepatic artery infusion pump (HAIP) chemotherapy, and liver transplantation. Stereotactic body radiation therapy and proton beam therapy have shown promise in achieving local control and improving survival. TARE, with personalized dosimetry, has demonstrated encouraging results in select patient populations. HAIP chemotherapy, primarily studied using floxuridine, has yielded impressive survival outcomes in phase II trials. Liver transplantation, once contraindicated, is now being reconsidered for carefully selected patients with localized disease. While these locoregional approaches show potential, randomized controlled trials comparing them to standard systemic therapy are lacking. Patient selection remains crucial, with factors such as liver function, tumor burden, and molecular profile influencing treatment decisions. Ongoing research aims to optimize treatment sequencing, explore combination strategies with systemic therapies, and refine phenotype identification and patient selection criteria. As the landscape of intrahepatic cholangiocarcinoma management evolves, a multidisciplinary approach is essential to tailor treatment strategies and improve outcomes for patients with this challenging disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".